Claude Opus 5.5 (effort default (no --effort flag) · thinking on) on Answer 6 multi-hop questions from ~150KB of meeting notes with corrections and decoys
AClaude Opus 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-16 · by @bobsiopener
- Estimated cost
- $0.14
- Wall time
- 17s
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt (this run)
# Task: answer questions from a year of meeting notes `meeting_notes.txt` holds ~400 meeting entries (≈220 KB). Facts are spread across meetings and some are later corrected, drafted, or rejected. Answer from the notes only. Write `answers.json`: {"q1": {"answer": "...", "meeting": <meeting number that is the authoritative source>}, ...} - q1: What capex was approved for the warehouse-robotics initiative? - q2: Who approved it? - q3: Who currently owns the contract with the lidar vendor for that initiative? - q4: Who chairs the security standup now? - q5: Which firmware version fixed the root cause of the lidar incident? - q6: When and where is the robotics lab moving (month and building)? No network.
Codename indirection, superseded/void figures, ownership hand-offs and postponed dates; must cite the authoritative meeting number. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).
Success criteria: 1. All 6 answers must contain the required token(s) for the authoritative (latest/approved) fact, case-insensitive. 2. Answers must not contain the superseded/void/decoy values for that question (any decoy present = wrong). 3. At least 5 of 6 cited meeting numbers must be the exact authoritative meeting.
Setup notes: Use Case Scout batch 4 case d10-long-context-needles (offline fixture). Prepared with batch4/prepare.sh; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored with the scout's scorer: `python score.py WORKDIR KEYDIR/key.json`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Rescored 2026-10-16 with Scout's fixed scorer (see batch4/CHANGES-2026-10-16.md). The original score was fail, and the model's output is unchanged. Claude Code's own reported cost for claude-opus-5.5: $0.140934. Score: pass. Cost is an ESTIMATE: measured tokens x pricing.json list price (Claude Pro subscription, nothing billed); input_tokens include cache reads and writes. Single run.
Estimated cost List-price estimate; not actually billed.
Metrics
- Estimated cost
- $0.14
- Wall time
- 17s
- Human step-ins
- 0
- Turns
- 4
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| AClaude Opus 5.5anthropic/claude-opus-5.5effort default (no --effort flag) · thinking on | 87,347 | 1,567 | $0.14 |
Reproduce this run
- Use the exact prompt shown above for this run (the use case page has the shared prompt).
- Same setup: Claude Opus 5.5 (anthropic/claude-opus-5.5, effort default (no --effort flag) · thinking on) via
Claude Code 2.1.299 (headless -p), cloud. - It counts as a success only if it meets every success criterion: 1. All 6 answers must contain the required token(s) for the authoritative (latest/approved) fact, case-insensitive. 2. Answers must not contain the superseded/void/decoy values for that question (any decoy present = wrong). 3. At least 5 of 6 cited meeting numbers must be the exact authoritative meeting.
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
Was this useful?
Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
[
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"stop_reason": "end_turn",
"session_id": "[REDACTED]",
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"cache_read_input_tokens": 75532,
"output_tokens": 1567,
"output_tokens_details": {
"thinking_tokens": 17
},
"server_tool_use": {
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"web_fetch_requests": 0
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"service_tier": "standard",
"cache_creation": {
"ephemeral_1h_input_tokens": 11807,
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"inference_geo": "global",
"iterations": [
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"type": "message"
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"speed": "standard",
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"webSearchRequests": 0,
"costUSD": 0.1409344,
"contextWindow": 1000000,
"maxOutputTokens": 128000,
"thinkingTokens": 17,
"canonicalModel": "claude-opus-5-5",
"provider": "firstParty",
"costBasis": "list"
}
},
"permission_denials": [],
"terminal_reason": "completed",
"fast_mode_state": "off",
"fast_mode_disabled_reason": "sdk_opt_in_required",
"subagent_stats": {
"spawned": 0,
"requested": {
"background": 0,
"foreground": 0,
"unset": 0
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"started_in_background": 0,
"max_depth": 0,
"spawned_by_subagents": 0,
"completed": 0,
"failed": 0,
"killed": {
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"refused": {
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"safety_stops": 0,
"is_error": false,
"num_turns": 4,
"subtype": "success",
"api_error_status": null,
"result": "I wrote `answers.json` and confirmed it parses as valid JSON.\n\nMost of each meeting is repeated filler, so I removed that and read the dozen or so entries with real decisions. The notes aren't always in date order, so I went by what each entry says it changes rather than its position in the file.\n\n| Q | Answer | Source meeting |\n|---|---|---|\n| q1 | EUR 2.4M capex | 311 |\n| q2 | Dalia Haddad (CFO delegate) | 311 |\n| q3 | Ines Duarte | 261 |\n| q4 | Hiro Sato | 201 |\n| q5 | Firmware 3.2.4 | 371 |\n| q6 | November, Building F | 331 |\n\nHow I handled the corrected, drafted and rejected items:\n- **Name:** the warehouse-robotics initiative is \"Project Kestrel\" (meeting 041). A draft name, \"Project Osprey,\" was proposed and later rejected (meeting 056).\n- **q1/q2:** meeting 151 discussed EUR 3.1M but didn't approve it. Meeting 311 approved EUR 2.4M and says the 3.1M figure is void.\n- **q3:** Erik Lund was named owner of the contract with the lidar vendor, Nordsense AB (meeting 091). Meeting 261 records that he handed it to Ines Duarte effective 2026-07-01.\n- **q4:** meeting 201 says Hiro Sato now chairs the security standup, replacing Chen Yu.\n- **q5:** a note on the lidar incident (INC-4471) first suspected a network outage, which was later disproved (meeting 366). The root cause was a certificate pinning bug in firmware 3.2.1, fixed in 3.2.4 (meeting 371).\n- **q6:** the lab was first set to move from Building C to Building F in September (meeting 121). Meeting 331 postponed it to November, still Building F.",
"ttft_ms": 2967,
"type": "result",
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"uuid": "[REDACTED]",
"ttft_stream_ms": 1065,
"time_to_request_ms": 271,
"first_content_frame_ms": 1065,
"queued_turn_count": 0,
"result_index": 0
}
]